ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2023
Evaluation and Prediction of Treatment Response for Hepatocellular Carcinoma.
Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Performance of Artificial Intelligence Models in Predicting Responsiveness of Hepatocellular Carcinoma to Transarterial Chemoembolization (TACE): A Systematic Review and Meta-Analysis.Journal of the American College of Radiology : JACR · 2026Pooled it
- Advances in the Therapeutic Landscape of Hepatocellular Carcinoma: Current Strategies and Future Perspectives.Cancers · 2026Review
- Gadoxetic acid-enhanced MRI in hepatocellular carcinoma: a comprehensive review of diagnostic, surveillance, and treatment response prediction and assessment.Japanese journal of radiology · 2026Review
- Assessment of viable tumours by [European journal of nuclear medicine and molecular imaging · 2025Article
- ALBI-sarcopenia score as a predictor of treatment outcomes in hepatocellular carcinoma.Scientific reports · 2025Article
- Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma.Computational and structural biotechnology journal · 2024Article
- Hepatocellular Carcinoma: The Evolving Role of Systemic Therapies as a Bridging Treatment to Liver Transplantation.Cancers · 2024Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The incidence of hepatocellular carcinoma (HCC) is still on the rise in North America and Europe and is the second leading cause of cancer-related mortality. The treatment of HCC varies, with surgery and locoregional therapy (LRT) such as radiofrequency ablation and transcatheter arterial chemoembolization, and radiation therapy being the primary treatment. Currently, systemic therapy with molecular-targeted agents and immune checkpoint inhibitors (ICIs) is becoming a major treatment option for the unresectable HCC. As the HCC after LRT or systemic therapy often remains unchanged in size and shows loss of contrast effect in contrast-enhanced CT or MRI, the response evaluation criteria in solid tumors (RECIST) and World Health Organization criteria, which are usually used to evaluate the treatment response of solid tumors, are not appropriate for HCC. The modified RECIST (mRECIST) and the European Association for the Study of the Liver (EASL) criteria were developed for HCC, with a focus on viable lesions. The latest 2018 edition of the Liver Imaging Reporting and Data System (LI-RADS) also includes a section on the evaluation of treatment response. The cancer microenvironment influences the therapeutic efficacy of ICIs. Several studies have examined the utility of gadoxetic acid-enhanced MRI for predicting the pathological and molecular genetic patterns of HCC. In the future, it may be possible to stratify prognosis and predict treatment response prior to systemic therapy by using pre-treatment imaging findings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.